This is the internal function upon which the iceberg wrapper is built. It performs standard
plugin lasso PPML estimation without fixed effects, relying on glmnet::glmnet. As the other
internals in the package, it needs a y vector and an x matrix.
plugin_lasso_int(
y,
x,
tol = 1e-08,
glmnettol = 1e-12,
penweights = NULL,
colcheck = FALSE,
K = 50,
verbose = FALSE,
lambda = NULL,
icepost = FALSE
)A list with 14 elements, including beta, which is the only one we use in the wrapper.
For a full list, see glmnet.
Dependent variable (a vector).
Regressor matrix.
Tolerance parameter for convergence of the IRLS algorithm.
Tolerance parameter to be passed on to glmnet::glmnet.
Optional: a vector of coefficient-specific penalties to use in plugin lasso.
Logical. If TRUE, checks for perfect multicollinearity in x.
Maximum number of iterations.
Logical. If TRUE, prints information to the screen while evaluating.
Penalty parameter (a number).
Logical. If TRUE, it carries out a post-lasso estimation with just the
selected variables and reports the coefficients from this regression.